# northamerica_canada_cana128 - Hobbs Lake - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# NOTE: Please cite Publication, and Online_Resource and date accessed when using these data.
# If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed.
#
#
# Online_Resource:
#
# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
#
# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/3450
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_canada_cana128 - Hobbs Lake - Breitenmoser Tree Ring Chronology Data
#--------------------
# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
#--------------------
# Description_and_Notes
#	Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details
#--------------------
# Publication
#	Authors: Breitenmoser, P.; Bronnimann, S.; Frank, D.
#	Published_Date_or_Year: 2014-03-11
#	Published_Title: Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies
#	Journal_Name: Climate of the Past
#	Volume: 10 
#	Edition:
#	Issue:
#	Pages: 437-449
#	DOI: 10.5194/cp-10-437-2014
#	Online_Resource: www.clim-past.net/10/437/2014/
#	Full_Citation:
#	Abstract: We investigate relationships between climate and tree-ring data on a global scale using the process-based VaganovÃÂ¢ÃÂÃÂShashkin Lite (VSL) forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a) to assess the VSL model performance by examining the relations between simulated and observed growth at 2287 globally distributed sites, (b) indentify optimal growth parameters found during the model calibration, and (c) to evaluate the potential of the VSL model as an observation operator for data-assimilation-based reconstructions of climate from tree-ring width. The assessment of the growth-onset threshold temperature of approximately 4ÃÂ¢ÃÂÃÂ6 C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level treering series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yielded notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL modelÃÂ¢ÃÂÃÂs ability to skilfully capture the climatic signal contained in tree-ring series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate.
#--------------------
#	Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig
#	Published_Date_or_Year: 2018
#	Published_Title: Additions to the last millennium reanalysis multi-proxy database
#	Journal_Name: Data Science Journal
#	Volume:
#	Edition:
#	Issue:
#	Pages:
#	Report_Number:
#	DOI:
#	Online_Resource:
#	Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal.
#	Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR).  The 2290 additional series include 2152 tree ring chronologies and 138 other series.  They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation.  A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project.  The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables.  Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods.
#------------------
# Funding_Agency
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant:
#--------------------
#	Funding_Agency_Name: National Science Foundation
#	Grant:AGS-1304263
#	Funding_Agency_Name: National Oceanic and Atmospheric Administration
#	Grant:NA14OAR4310176
#------------------
# Site_Information
#	Site_Name: Hobbs Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 46.72
#	Southernmost_Latitude: 46.72
#	Easternmost_Longitude: -80.2
#	Westernmost_Longitude: -80.2
#	Elevation: 500 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_canada_cana128B
#	Earliest_Year: 1712
#	Most_Recent_Year: 1993
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.36649628659","T2":"14.906914354","M1":"0.0228908570621","M2":"0.224979612046"}}
#--------------------
# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
#--------------------
# Chronology:
#
#
#
#--------------------
# Variables
#
# Data variables follow that are preceded by ## in columns one and two.
# Data line variables format:  Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data)
#
##age	age, , ,years AD, , , , ,N
##trsgi	tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1712	0.88
1713	1.157
1714	0.963
1715	1.158
1716	0.794
1717	0.741
1718	1.047
1719	0.974
1720	0.978
1721	0.792
1722	0.857
1723	0.647
1724	0.742
1725	0.867
1726	0.946
1727	1.055
1728	1.083
1729	1.006
1730	0.879
1731	0.949
1732	0.976
1733	0.814
1734	0.996
1735	0.895
1736	0.723
1737	0.988
1738	0.954
1739	0.715
1740	0.614
1741	0.475
1742	0.334
1743	0.315
1744	0.314
1745	0.415
1746	0.52
1747	0.651
1748	0.697
1749	0.96
1750	1.123
1751	0.924
1752	0.78
1753	0.756
1754	1.027
1755	1.007
1756	1.32
1757	0.861
1758	0.867
1759	0.83
1760	0.895
1761	1.027
1762	1.165
1763	1.369
1764	1.34
1765	1.372
1766	1.24
1767	1.242
1768	1.246
1769	1.198
1770	0.961
1771	1.001
1772	1.03
1773	1.015
1774	1.138
1775	1.246
1776	0.94
1777	1.119
1778	1.102
1779	0.908
1780	0.949
1781	1.048
1782	1.291
1783	0.99
1784	1.215
1785	0.94
1786	0.988
1787	0.962
1788	0.957
1789	1.013
1790	1.008
1791	0.946
1792	0.556
1793	0.939
1794	0.775
1795	0.867
1796	1.021
1797	0.855
1798	0.82
1799	1.021
1800	1.155
1801	1.257
1802	1.281
1803	1.032
1804	1.257
1805	1.204
1806	1.388
1807	1.369
1808	1.083
1809	1.015
1810	0.956
1811	1.044
1812	1.367
1813	1.27
1814	1.435
1815	1.481
1816	1.432
1817	1.364
1818	1.01
1819	1.173
1820	0.793
1821	0.869
1822	0.952
1823	0.97
1824	0.996
1825	1.085
1826	0.995
1827	1.191
1828	1.26
1829	1.134
1830	1.273
1831	1.212
1832	1.072
1833	1.177
1834	1.149
1835	1.02
1836	0.74
1837	0.696
1838	0.481
1839	0.21
1840	0.184
1841	0.259
1842	0.359
1843	0.524
1844	0.635
1845	0.883
1846	1.027
1847	0.831
1848	1.134
1849	0.734
1850	0.869
1851	0.961
1852	1.069
1853	1.204
1854	1.094
1855	1.092
1856	1.3
1857	1.112
1858	0.886
1859	1.094
1860	0.813
1861	0.836
1862	0.854
1863	0.991
1864	0.726
1865	0.842
1866	0.916
1867	1.023
1868	0.747
1869	0.914
1870	0.963
1871	1.341
1872	1.209
1873	1.309
1874	1.019
1875	0.943
1876	0.604
1877	0.893
1878	0.882
1879	0.955
1880	0.923
1881	1.013
1882	0.989
1883	1.003
1884	1.182
1885	1.248
1886	1.043
1887	1.109
1888	1.063
1889	1.302
1890	0.995
1891	0.991
1892	1.229
1893	1.161
1894	1.073
1895	1.072
1896	1.342
1897	1.186
1898	1.561
1899	1.291
1900	1.102
1901	1.05
1902	1.27
1903	1.447
1904	1.432
1905	1.475
1906	1.34
1907	1.144
1908	1.228
1909	1.066
1910	0.997
1911	1.064
1912	1.25
1913	1.258
1914	1.144
1915	1.217
1916	1.002
1917	0.899
1918	0.89
1919	0.678
1920	0.875
1921	0.822
1922	0.985
1923	0.782
1924	0.824
1925	0.911
1926	0.844
1927	0.798
1928	0.606
1929	0.837
1930	0.954
1931	1.049
1932	1.341
1933	1.234
1934	0.825
1935	0.824
1936	0.825
1937	0.83
1938	0.922
1939	1.022
1940	1.023
1941	0.828
1942	1.221
1943	0.73
1944	0.802
1945	0.93
1946	0.944
1947	0.88
1948	0.82
1949	0.835
1950	1.027
1951	1.169
1952	0.9
1953	1.292
1954	1.289
1955	1.182
1956	1.051
1957	0.84
1958	0.945
1959	0.879
1960	0.678
1961	0.861
1962	0.554
1963	0.598
1964	0.819
1965	0.67
1966	0.538
1967	0.472
1968	0.468
1969	0.449
1970	0.65
1971	0.608
1972	0.523
1973	0.63
1974	0.817
1975	0.948
1976	0.866
1977	1.075
1978	1.071
1979	1.123
1980	1.044
1981	0.89
1982	0.988
1983	0.941
1984	1.056
1985	1.217
1986	1.076
1987	1.185
1988	1.184
1989	1.268
1990	1.107
1991	1.104
1992	1.224
1993	1.045